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Deep Dives

Series

October 2026

  1. API Rate Limits Compared: Every Major LLM Provider (October 2026)

    API rate limits for every major LLM provider — October 17, 2026. Side-by-side tables for OpenAI, Anthropic, Google, Groq, xAI, DeepSeek, Mistral, Cerebras, SambaNova, and more.
  2. LLM Token Costs and Efficiency: A Practitioner's Guide (October 2026)

    LLM token costs across 15+ providers: per-token pricing, caching mechanics, batch discounts, model routing, and cost optimization for October 2026.
  3. Orchestrating Long-Running AI Workflows: Durable Execution, Checkpointing, and Human-in-the-Loop for AI Pipelines

    How token-aware rate limiting works for LLM APIs, why request-count limits fail, and implementation patterns across API gateways and proxy layers.
  4. Orchestrating Long-Running AI Workflows: Durable Execution, Checkpointing, and Human-in-the-Loop for AI Pipelines

    How orchestrating long-running AI workflows differs from traditional job queues — durable execution, checkpointing, human-in-the-loop, and practical…

September 2026

  1. The Open-Source AI Inference Stack: Ollama, vLLM, llama.cpp, LiteLLM, and the Tooling That Makes Self-Hosted Inference Practical

    How the open-source AI inference stack fits together: Ollama, vLLM, llama.cpp, LiteLLM, and the tooling that makes self-hosted models practical in 2026.
  2. AI Agent Authentication and Identity: From Shared API Keys to Workload Identity

    Every major AI authentication pattern explained: API keys, OAuth 2.0, workload identity, DPoP tokens, and scoped credentials for agent-to-API…
  3. Token-Based Rate Limiting for LLM APIs

    How token-aware rate limiting works for LLM APIs: algorithms, implementation patterns, sliding windows, and production architectures across API gateways.
  4. API Rate Limits Compared: Every Major LLM Provider (September 2026)

    API rate limits for every major LLM provider — September 10, 2026. Side-by-side tables for OpenAI, Anthropic, Google, Groq, xAI, DeepSeek, Mistral, Cerebras, SambaNova, and more.
  5. LLM Token Costs and Efficiency: A Practitioner's Guide (September 2026)

    LLM token costs across 15+ providers: per-token pricing, caching mechanics, batch discounts, model routing, and cost optimization for September 2026.
  6. AI Guardrails for Production Systems

    How AI guardrails work in production: input validation, output filtering, PII detection, hallucination detection, and the architecture that ties them together.
  7. Semantic Caching for LLM Applications

    Technical breakdown of semantic caching for LLM apps: exact vs embedding-based matching, similarity thresholds, cache invalidation, and the real tradeoffs.

August 2026

  1. LLM Gateway Architecture: Managing Multiple AI Providers Through a Unified API Layer

    How LLM gateways work: provider abstraction, fallback routing, load balancing, cost tracking, and credential management across OpenAI, Anthropic,…
  2. The GPU Landscape for AI Inference: H100 vs A100 vs L40S vs Consumer GPUs, Cloud Pricing, and the Self-Host vs API Decision

    Every major AI provider handles GPU memory, batching, and model serving differently. This is how the inference stack works from HTTP request to matrix…
  3. Prompt Engineering from First Principles

    How prompt engineering techniques work at the mechanical level — tokenization, attention patterns, sampling parameters, and why chain-of-thought…
  4. API Rate Limits Compared: Every Major LLM Provider (August 2026)

    API rate limits for every major LLM provider — August 10, 2026. Side-by-side tables for OpenAI, Anthropic, Google, Groq, xAI, DeepSeek, Mistral, Cerebras, SambaNova, and more.
  5. LLM Token Costs and Efficiency: A Practitioner's Guide (August 2026)

    LLM token costs across 15+ providers: per-token pricing, caching mechanics, batch discounts, model routing, and cost optimization for August 2026.

July 2026

  1. Fine-Tuning vs RAG vs Long Context: Decision Framework with Real Tradeoffs

    Every major fine-tuning approach compared against RAG and long-context prompting — with architecture patterns, cost math, latency profiles, and a…
  2. Multi-Modal AI in Practice: Vision, Audio, and Document Understanding Across Every Major Provider

    A complete technical guide to multi-modal AI: vision, audio, and document understanding across Claude, GPT, Gemini, and open models, with architecture…
  3. API Rate Limits Compared: Every Major LLM Provider (July 2026)

    API rate limits for every major LLM provider — July 10, 2026. Side-by-side tables for OpenAI, Anthropic, Google, Groq, xAI, DeepSeek, Mistral, Cerebras, SambaNova, and more.
  4. LLM Token Costs and Efficiency: A Practitioner's Guide (July 2026)

    LLM token costs across 15+ providers: per-token pricing, caching mechanics, batch discounts, model routing, and cost optimization for July 2026.
  5. Streaming, SSE, and Real-Time AI: How Streaming Responses Work and How to Build Responsive AI UIs

    Every major AI provider handles streaming differently. This guide covers SSE, WebSockets, HTTP chunked transfer, and the implementation details that…
  6. LLM Evaluation and Benchmarks: What They Measure, What They Miss, and How to Evaluate for Your Use Case

    How LLM evaluation benchmarks actually work, what they measure, what they miss, and how to build evaluation that matters for your specific application.

June 2026

  1. API Rate Limits Compared: Every Major LLM Provider (June 2026)

    API rate limits for every major LLM provider — June 13, 2026. Side-by-side tables for OpenAI, Anthropic, Google, Groq, xAI, DeepSeek, Mistral, Cerebras, SambaNova, and more.
  2. LLM Token Costs and Efficiency: A Practitioner's Guide (June 2026)

    LLM token costs across 15+ providers: per-token pricing, caching mechanics, batch discounts, model routing, and cost optimization for June 2026.
  3. API Rate Limits Compared: Every Major LLM Provider (June 2026)

    API rate limits for every major LLM provider — June 2026. Side-by-side tables for OpenAI, Anthropic, Google, Groq, xAI, DeepSeek, Mistral, Cerebras, SambaNova, and more.
  4. LLM Token Costs and Efficiency: A Practitioner's Guide (June 2026)

    LLM token costs across 15+ providers: per-token pricing, caching mechanics, batch discounts, model routing, and cost optimization for June 2026.

May 2026

  1. API Rate Limits Compared: Every Major LLM Provider (May 2026)

    API rate limits for every major LLM provider — May 2026. Side-by-side tables for OpenAI, Anthropic, Google, Groq, xAI, DeepSeek, Mistral, Cerebras, SambaNova, and more.
  2. LLM Token Costs and Efficiency: A Practitioner's Guide (May 2026)

    LLM token costs across 15+ providers: per-token pricing, caching mechanics, batch discounts, model routing, and cost optimization for May 2026.
  3. Cost Optimization for LLM Applications

  4. API Rate Limits Compared: Every Major LLM Provider (May 2026)

    API rate limits for every major LLM provider — May 2026. Side-by-side tables for OpenAI, Anthropic, Google, Groq, xAI, DeepSeek, Mistral, Cerebras, SambaNova, and more.
  5. LLM Token Costs and Efficiency: A Practitioner's Guide (May 2026)

    LLM token costs across 15+ providers: per-token pricing, caching mechanics, batch discounts, model routing, and cost optimization for May 2026.
  6. LLM Observability in Production

  7. CI/CD for AI Applications

  8. Structured Output from LLMs

April 2026

  1. Building Reliable RAG Systems

  2. API Rate Limits Compared: Every Major LLM Provider (April 2026)

    Side-by-side rate limit comparison across 17 LLM API providers — OpenAI, Anthropic, Google, Groq, xAI, DeepSeek, Mistral, Cerebras, SambaNova, Perplexity, Alibaba, Moonshot, and more — as of April 2026.
  3. LLM Token Costs and Efficiency: A Practitioner's Guide (April 2026)

    Beyond the pricing page. How to actually think about LLM costs: per-token pricing across 15+ providers, hidden multipliers, caching mechanics, batch discounts, model routing architectures, and what 'cost per useful output' means in production.
  4. AI Agent Orchestration Patterns

  5. How Vector Databases Actually Work

  6. Create collection with scalar quantization

  7. Local LLM on a $550 AMD Mini PC: 28B Models at 20 tok/s

    AMD 780M iGPU + 64GB DDR5 runs Gemma 4 28B at 19.5 tok/s. Setup guide, benchmarks, and cost breakdown vs. Mac Mini for local LLM inference under $600.

March 2026

  1. Embeddings in Practice: Every Major Model Compared

  2. omlx: Run Local LLMs on Apple Silicon with a RAG Customer Support App

    omlx: macOS-native LLM server for Apple Silicon with SSD KV caching that cuts cold-start prefill from 90s to under 5s. Complete RAG customer support chatbot tutorial included.
  3. Prompt Injection Prevention in Production

    Taxonomy of prompt injection attacks and the layered defenses — input validation, output filtering, guardrails — that actually work at scale.
  4. The Inference Stack Top to Bottom

    What happens between your API call and a streamed token — routing, batching, KV cache, quantization, and speculative decoding explained.
  5. MCP, Tool Use, and Function Calling: How Agents Actually Work in 2026

    A comprehensive rundown of function calling, Model Context Protocol, agent frameworks, and the patterns that actually work in production — across every major provider.
  6. API Rate Limits Compared: Every Major LLM Provider in One Place

    A side-by-side comparison of rate limits across 15 LLM API providers — OpenAI, Anthropic, Google, Groq, xAI, DeepSeek, Mistral, Perplexity, Alibaba, Moonshot, and more — as of March 2026.